Triple
T4276533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OpenAPI |
E97058
|
entity |
| Predicate | isLanguageAgnostic |
P33278
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [OpenAPI, isLanguageAgnostic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLanguageAgnostic Context triple: [OpenAPI, isLanguageAgnostic, true]
-
A.
isLanguageIndependent
chosen
Indicates that the relationship, property, or behavior holds true regardless of the specific natural language used to express or encode it.
-
B.
languageNeutral
Indicates that the relationship or action is independent of any specific natural language, applying uniformly across different linguistic contexts.
-
C.
isProgrammingLanguageIndependent
Indicates that something (such as a concept, algorithm, or interface) does not depend on any specific programming language and can be applied or used across different languages.
-
D.
isWorldLanguage
Indicates that a language is widely used across multiple countries or regions and serves as a common means of communication beyond its original native community.
-
E.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501d677481909e7416a1d2b0008c |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.